Probabilistic method
Builds on Probability spaceEventExpected value
Definition
Let be a nonempty finite set of objects and let be a property that objects in may have. A proof by the probabilistic method that some element of has does the following:
- It puts a probability measure on , making it a probability space.
- It shows that the event has positive probability.
- It concludes that this event is nonempty, so some element of has .
A common form of step 2 uses a random variable on : if the expected value satisfies , then for some .
Remarks
Erdős' bound for diagonal Ramsey numbers is an example. Let and , and colour each edge of the complete graph red or blue independently with probability . The expected number of monochromatic copies of is , and this is less than . So some colouring has no monochromatic , and the Ramsey number satisfies . An argument that only shows that the event has probability at least is not a proof by this method. Step 2 fails there, and an event of probability may be empty. The method also applies to infinite probability spaces, with the same conclusion that an event of positive probability is nonempty.
Reading path
To understand this page from the ground up, read these 4 pages in order. The foundations come first.
Show the path as a graph
- no evidence level
- Event concept
- Expected value concept
- Probability space concept
- Probabilistic method definition
Further reading
About this page
| Tag | AVD8S4NW3B |
|---|---|
| URI | m2://AVD8S4NW3B |
| Kind | definition |
| Writing | W0 stub |
| MSC | 05D40, 60C05 |
| Defines | Probabilistic method |
| Uses | Probability space, Event, Expected value |
| Changed | 2 November 2026 |
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